Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: identifying, by one or more processors, a user input providing a query for digital content; identifying, by the one or more processors, a response to the query, the response including one or more digital content items corresponding to the query for the digital content; determining, by the one or more processors, at least one keyword included in the one or more digital content items; generating, by the one or more processors, a respective customized blacklist of terms for each of the respective one or more digital content items, the respective customized generated blacklists including the determined at least one keyword; sending, by the one or more processors, a first respective customized blacklist corresponding to a first digital content item of the respective one or more digital content items to a listening device, wherein the first respective customized blacklist includes an active time length for the first respective customized blacklist based at least in part on a defined time-frame of metadata of the first digital content item; and in response to an expiration of the active time length, removing, by the one or more processors, the first respective customized blacklist corresponding to the first digital content item from the listening device.
This invention relates to a system for dynamically managing content filtering in response to user queries. The method involves processing a user input query to retrieve relevant digital content, such as audio or video files, from a database. The system analyzes the retrieved content to identify key terms or keywords within the content items. For each content item, a customized blacklist of terms is generated, incorporating the identified keywords. These blacklists are then transmitted to a listening device, such as a smart speaker or headphones, to filter out unwanted content during playback. Each blacklist is assigned an active time length based on metadata associated with the content item, such as its duration or relevance period. Once the active time length expires, the blacklist is automatically removed from the listening device to prevent further filtering. This approach ensures that content filtering is contextually relevant and time-bound, improving user experience by dynamically adapting to the content being accessed. The system may also apply similar filtering to other content items retrieved in response to the query, each with their own customized blacklists and time-based expiration.
2. The method of claim 1 , wherein determining the at least one keyword included in the one or more digital content items, further comprises: identifying, by the one or more processors, at least one trigger word in the one or more digital content items that corresponds to a wake-up command of the listening device; identifying, by the one or more processors, words adjacent to the at least one trigger word; and determining, by the one or more processors, the at least one keyword included in the one or more digital content items based on the at least one trigger word in the one or more digital content items and the identified words adjacent to the at least one trigger word in the one or more digital content items.
This invention relates to digital content analysis for listening devices, specifically improving keyword detection in audio or text data. The problem addressed is the difficulty in accurately identifying relevant keywords in digital content, particularly when the content includes noise or irrelevant information. The solution involves a method for extracting keywords from digital content by analyzing trigger words and their adjacent words. The method operates by first identifying at least one trigger word in the digital content that matches a wake-up command recognized by the listening device. These trigger words act as indicators of relevant content. Next, the system identifies words adjacent to the trigger word, which may include contextually relevant information. Finally, the system determines the keywords based on both the trigger word and the adjacent words, ensuring that the extracted keywords are meaningful and contextually accurate. This approach enhances the precision of keyword extraction by leveraging the relationship between trigger words and nearby terms, reducing false positives and improving the relevance of the detected keywords. The method is particularly useful in applications such as voice assistants, transcription services, and automated content analysis where accurate keyword detection is critical.
3. The method of claim 1 , wherein generating the respective customized blacklist of terms for each of the respective one or more digital content items, further comprises: determining, by the one or more processors, a time length of each of the one or more digital content items from metadata of each of the one or more digital content items; defining, by the one or more processors, a time-frame that each of the respective customized generated blacklists are active based on the determined time length of each of the one or more digital content items; and adding, by the one or more processors, the defined time-frame to each of the respective customized generated blacklists of terms that correspond to each of the one or more digital content items.
This invention relates to digital content processing, specifically methods for generating and applying customized blacklists of terms to digital content items. The problem addressed is the need to dynamically filter or restrict certain terms in digital content based on context, such as the duration or time length of the content. The invention improves upon existing systems by creating time-sensitive blacklists that are tailored to individual digital content items, ensuring that restricted terms are only blocked during specific time frames relevant to the content. The method involves analyzing metadata of digital content items to determine their time length. Based on this duration, a time frame is defined for each content item, during which a customized blacklist of terms will be active. The blacklist is then generated and associated with the content item, including the defined time frame. This ensures that the blacklist is only applied during the specified period, allowing for context-aware term filtering. The system dynamically adjusts the blacklist's activation based on the content's duration, improving relevance and reducing unnecessary restrictions outside the intended time frame. This approach enhances content moderation by aligning term restrictions with the temporal context of the content.
4. The method of claim 1 , further comprising: determining, by the one or more processors, that the user initiates the first digital content item of the one or more digital content items.
A system and method for managing digital content playback involves detecting user interactions with digital content items, such as videos or audio files, and dynamically adjusting playback behavior based on those interactions. The system monitors user actions, such as selecting or initiating playback of a digital content item, and processes this input to determine the user's intent. For example, when a user starts playing a digital content item, the system identifies this action and may trigger additional functions, such as pausing other content, adjusting playback settings, or retrieving related content. The system uses one or more processors to analyze the user's interaction and execute the appropriate response, ensuring seamless and personalized content playback. This approach enhances user experience by automating playback adjustments in response to direct user input, reducing manual intervention and improving content accessibility. The method is particularly useful in multimedia applications where multiple content items may be available, and the system must prioritize or manage playback based on user preferences or actions.
5. The method of claim 1 , wherein determining the at least one keyword included the one or more digital content items, further comprises: in response to receiving the response including the one or more digital content items corresponding to the query for digital content, identifying, by the one or more processors, at least one word in each of the respective one or more digital content items that corresponds to a wake-up command of the listening device.
This invention relates to a system for processing digital content queries and identifying wake-up commands within retrieved content. The technology addresses the challenge of detecting specific trigger phrases or keywords in digital content items that are responsive to user queries, particularly for devices that rely on wake-up commands to activate or respond. When a user submits a query for digital content, the system retrieves one or more relevant digital content items. Upon receiving these items, the system analyzes each one to identify at least one word that matches a predefined wake-up command for a listening device. The wake-up command is a specific phrase or keyword that triggers the device to transition from an inactive to an active state, enabling further interaction. The system processes the content items to extract these keywords, ensuring that the listening device can accurately detect and respond to the wake-up command when encountered in the retrieved content. This method enhances the functionality of listening devices by improving their ability to recognize and act upon wake-up commands embedded within digital content.
6. The method of claim 1 , wherein generating the respective customized blacklist of terms for each of the one or more digital content items, the respective customized generated blacklists including the determined at least one keyword, further comprises: adding, by the one or more processors, the determined at least one keyword included in the one or more digital content items to a pre-existing blacklist file associated with the listening device.
This invention relates to digital content processing, specifically methods for generating and managing customized blacklists of terms to filter or restrict content in digital content items. The problem addressed is the need to dynamically update and personalize blacklists for content filtering, particularly in systems where digital content items may contain terms that should be excluded or restricted based on user preferences, regulatory requirements, or other criteria. The method involves analyzing one or more digital content items to identify at least one keyword that should be excluded or restricted. Once identified, these keywords are added to a pre-existing blacklist file associated with a listening device, such as a smart speaker, virtual assistant, or other audio processing system. The blacklist file is used to filter or block content containing the identified keywords during playback or processing. The method ensures that the blacklist is dynamically updated to reflect new or previously unrecognized terms that should be restricted, improving content filtering accuracy and personalization. The system may also account for context, such as user preferences or regional regulations, to determine which terms should be added to the blacklist. This approach enhances content moderation by adapting to evolving content and user needs.
7. A computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to identify a user input providing a query for digital content; program instructions to identify a response to the query, the response including one or more digital content items corresponding to the query for the digital content; program instructions to determine at least one keyword included in the one or more digital content items; program instructions to generate a respective customized blacklist of terms for each of the respective one or more digital content items, the respective customized generated blacklists including the determined at least one keyword; program instructions to send a first respective customized blacklist corresponding to a first digital content item of the respective one or more digital content items to a listening device, wherein the first respective customized blacklist includes an active time length for the first respective customized blacklist based at least in part on a defined time-frame of metadata of the first digital content item; and in response to an expiration of the active time length, program instructions to remove the first respective customized blacklist corresponding to the first digital content item from the listening device.
This invention relates to a system for managing digital content queries and filtering responses using dynamic blacklists. The problem addressed is the need to prevent unwanted content from being accessed or played back after a user queries for digital content, particularly in scenarios where the content may contain sensitive or time-sensitive information. The solution involves a computer program product that processes user queries, identifies relevant digital content, and generates customized blacklists of terms for each content item. These blacklists include keywords extracted from the content and are sent to a listening device, such as a voice assistant or audio playback system. Each blacklist has an active time length based on metadata associated with the content, such as its duration or relevance period. Once the active time length expires, the blacklist is automatically removed from the listening device. This ensures that the filtering is temporary and aligned with the content's lifecycle, preventing unintended access to outdated or irrelevant terms. The system dynamically adjusts filtering based on content metadata, improving user experience and security.
8. The computer program product of claim 7 , wherein the program instructions to determine the at least one keyword included in the one or more digital content items, further comprise program instructions to: identify at least one trigger word in the one or more digital content items that corresponds to a wake-up command of the listening device; identify words adjacent to the at least one trigger word; and determine the at least one keyword included in the one or more digital content items based on the at least one trigger word in the one or more digital content items and the identified words adjacent to the at least one trigger word in the one or more digital content items.
This invention relates to a computer program product for processing digital content to identify keywords, particularly in the context of voice-activated or listening devices. The technology addresses the challenge of accurately detecting and extracting relevant keywords from digital content, such as audio or text, to improve the responsiveness of listening devices to user commands. The program analyzes digital content to identify trigger words that correspond to wake-up commands for a listening device. Once a trigger word is detected, the program examines adjacent words to determine the context and relevance of the trigger word. By combining the trigger word with its surrounding words, the program can accurately identify and extract at least one keyword from the digital content. This process enhances the listening device's ability to recognize and respond to user commands more effectively, reducing false activations and improving command accuracy. The invention ensures that the listening device can distinguish between accidental trigger words and intentional commands by evaluating the surrounding linguistic context. This method improves the efficiency and reliability of voice-activated systems, making them more responsive to user needs. The program instructions are designed to work seamlessly with existing listening devices, providing a robust solution for keyword extraction in digital content processing.
9. The computer program product of claim 7 , wherein the program instructions to generate the respective customized blacklist of terms for each of the respective one or more digital content items, further comprise program instructions to: determine a time length of each of the one or more digital content items from metadata of each of the one or more digital content items; define a time-frame that each of the respective customized generated blacklists are active based on the determined time length of each of the one or more digital content items; and add the defined time-frame to each of the customized generated blacklist of terms that correspond to each of the one or more digital content items.
This invention describes a system that processes a user's query for digital content to identify relevant content items. It then determines specific keywords embedded within these digital content items. To manage potential interactions with a listening device, the system generates a customized blacklist of terms for each digital content item, including these identified keywords. Critically, during this blacklist generation, the system first calculates the *duration* of each digital content item by extracting its time length from its metadata. Based on this determined duration, it then defines a specific *active time-frame* for each corresponding customized blacklist. This defined active time-frame is subsequently added to the blacklist, which is then sent to the listening device. This ensures the blacklist is active only for the relevant period, after which it is automatically removed from the device.
10. The computer program product of claim 7 , further comprising program instructions, stored on the one or more computer readable storage media, to: determine that the user initiates the first digital content item of the one or more digital content items.
This invention relates to digital content management systems, specifically addressing the challenge of efficiently tracking and responding to user interactions with digital content. The system involves a computer program product that monitors and processes user engagement with digital content items, such as documents, media files, or applications, stored on one or more computer-readable storage media. The program includes instructions to detect when a user initiates interaction with a specific digital content item from a collection of such items. This detection may involve identifying user actions like opening, launching, or otherwise accessing the content. The system may also include additional functionalities, such as analyzing user behavior patterns, logging interaction data, or triggering automated responses based on the detected initiation. The invention aims to improve user experience and system efficiency by dynamically responding to user actions in real-time, ensuring seamless and personalized content delivery. The program operates within a computing environment where digital content is stored and accessed, leveraging storage media to execute the necessary instructions for monitoring and processing user interactions.
11. The computer program product of claim 7 , wherein program instructions to determine the at least one keyword included the one or more digital content items, further comprise program instructions to: in response to receiving the response including the one or more digital content items corresponding to the query for digital content, identify at least one word in each of the respective one or more digital content items that corresponds to a wake-up command of the listening device.
This invention relates to a computer program product for processing digital content in response to user queries, particularly for identifying and responding to wake-up commands in digital content items. The system receives a query for digital content and retrieves one or more digital content items corresponding to the query. The program then analyzes each content item to identify at least one word that matches a predefined wake-up command for a listening device. The wake-up command is a specific word or phrase that triggers the listening device to transition from a low-power or inactive state to an active state, ready to receive further commands or perform actions. The identified wake-up command enables the listening device to respond appropriately to subsequent user inputs or instructions. This invention enhances the functionality of listening devices by ensuring they can detect and respond to wake-up commands embedded within digital content, improving user interaction and device responsiveness. The system may be integrated into various applications, such as voice assistants, smart speakers, or other audio processing systems, to provide seamless and efficient command recognition.
12. The computer program product of claim 7 , wherein program instructions to generate the respective customized blacklist of terms for each of the one or more digital content items, the respective customized generated blacklists including the determined at least one keyword, further comprise program instructions to: add the determined at least one keyword included in the one or more digital content items to a pre-existing blacklist file associated with the listening device.
This invention relates to digital content filtering for listening devices, addressing the challenge of dynamically blocking unwanted terms in real-time audio processing. The system generates customized blacklists of terms for digital content items, such as audio streams or files, to filter out specific keywords or phrases. The process involves analyzing the content to identify keywords that should be excluded, then integrating these keywords into a pre-existing blacklist file linked to the listening device. This blacklist file is used to filter or modify the content during playback, ensuring unwanted terms are either removed or altered. The system may also include additional steps such as analyzing user preferences, historical data, or contextual factors to refine the blacklist. The invention improves user experience by dynamically adapting to content and user needs, reducing the need for manual updates to the blacklist. The solution is particularly useful in applications like smart speakers, voice assistants, or audio processing systems where real-time filtering is required.
13. A computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify a user input providing a query for digital content; program instructions to identify a response to the query, the response including one or more digital content items corresponding to the query for the digital content; program instructions to determine at least one keyword included in the one or more digital content items; program instructions to generate a respective customized blacklist of terms for each of the respective one or more digital content items, the respective customized generated blacklists including the determined at least one keyword; program instructions to send a first respective customized blacklist corresponding to a first digital content item of the respective one or more digital content items to a listening device, wherein the first respective customized blacklist includes an active time length for the first respective customized blacklist based at least in part on a defined time-frame of metadata of the first digital content item; and in response to an expiration of the active time length, program instructions to remove the first respective customized blacklist corresponding to the first digital content item from the listening device.
This invention relates to a computer system for managing digital content queries and filtering responses using dynamic blacklists. The system addresses the problem of irrelevant or unwanted content appearing in search results by automatically generating and applying customized blacklists to filter out specific terms from digital content items. The system includes one or more processors and storage media with program instructions to process user queries, identify relevant digital content, and extract keywords from those items. For each content item, a customized blacklist is generated, incorporating the extracted keywords. These blacklists are sent to a listening device, such as a user's device, with an active time length based on metadata associated with the content item, such as its duration or relevance period. Once the active time length expires, the blacklist is automatically removed from the listening device. This approach ensures that the filtering is contextually relevant and time-bound, improving the accuracy and efficiency of content filtering without requiring manual updates. The system dynamically adapts to the content being accessed, reducing the likelihood of outdated or irrelevant filters affecting future searches.
14. The computer system of claim 13 , wherein program instructions to determine the at least one keyword included in the one or more digital content items, further comprise program instructions to: identify at least one trigger word in the one or more digital content items that corresponds to a wake-up command of the listening device; identify words adjacent to the at least one trigger word; and determine the at least one keyword included in the one or more digital content items based on the at least one trigger word in the one or more digital content items and the identified words adjacent to the at least one trigger word in the one or more digital content items.
A computer system processes digital content to identify keywords, particularly in relation to voice-activated listening devices. The system extracts keywords from digital content by first detecting trigger words that match wake-up commands for the listening device. Once a trigger word is identified, the system analyzes adjacent words to determine relevant keywords. This approach ensures that the system accurately captures contextually significant terms following a wake-up command, improving the precision of keyword extraction for voice-based interactions. The method enhances the listening device's ability to respond appropriately to user queries by focusing on keywords that are most likely to be part of a command or request. This technique is particularly useful in applications where digital content must be parsed for actionable instructions or information retrieval, such as in smart assistants or automated transcription services. The system's reliance on trigger words and adjacent word analysis ensures that the extracted keywords are contextually relevant, reducing the likelihood of irrelevant or misleading results.
15. The computer system of claim 13 , wherein the program instructions to generate the respective customized blacklist of terms for each of the respective one or more digital content items, further comprise program instructions to: determine a time length of each of the one or more digital content items from metadata of each of the one or more digital content items; define a time-frame that each of the respective customized generated blacklist are active based on the determined time length of each of the one or more digital content items; and add the defined time-frame to each of the customized generated blacklist of terms that correspond to each of the one or more digital content items.
This invention relates to a computer system for generating and applying customized blacklists of terms to digital content items, such as videos or audio files, to filter out unwanted content. The system addresses the challenge of dynamically adapting blacklists to the specific characteristics of each digital content item, ensuring that filtering is contextually relevant and time-sensitive. The system determines the time length of each digital content item by analyzing its metadata, then defines an active time-frame for each customized blacklist based on this duration. For example, a blacklist for a 10-minute video would be active only during that playback period. The time-frame is added to the blacklist, ensuring that the filtering rules apply only during the relevant segment of the content. This approach prevents over-filtering or under-filtering by aligning the blacklist's active period with the content's actual runtime. The system may also generate multiple blacklists for different segments of a single content item, allowing for granular control over filtering. For instance, a video with distinct scenes could have separate blacklists for each scene, each with its own time-frame. This ensures that terms are filtered only when they are contextually inappropriate, improving user experience and content accuracy. The invention enhances content moderation by dynamically adjusting filtering rules to the temporal structure of digital media.
16. The computer system of claim 13 , further comprising program instructions, stored on the computer readable storage media for execution by at least one of the one or more processors, to: determine that the user initiates the first digital content item of the one or more digital content items.
This invention relates to a computer system for managing digital content items, particularly focusing on user interactions with such content. The system addresses the challenge of efficiently tracking and responding to user actions within a digital environment, such as selecting or initiating digital content items like documents, media files, or applications. The system includes one or more processors and computer-readable storage media storing program instructions. These instructions enable the system to detect when a user initiates a first digital content item from a set of available digital content items. The system may also include additional functionalities, such as analyzing user behavior, managing content access, or triggering automated responses based on the detected initiation. The invention aims to improve user experience by dynamically adapting to user interactions, ensuring seamless and personalized content delivery. The system's ability to monitor and respond to user actions in real-time enhances efficiency and interactivity in digital environments.
17. The computer system of claim 13 , wherein the program instructions to determine the at least one keyword included the one or more digital content items, further comprise program instructions to: in response to receiving the response including the one or more digital content items corresponding to the query for digital content, identify at least one word in each of the respective one or more digital content items that corresponds to a wake-up command of the listening device.
This invention relates to a computer system for processing digital content queries, particularly focusing on identifying wake-up commands within retrieved content. The system addresses the challenge of efficiently detecting and responding to specific voice commands, such as wake-up triggers, in digital content retrieved in response to user queries. The system receives a query for digital content and processes a response that includes one or more digital content items. Upon receiving the response, the system analyzes each content item to identify at least one word that matches a predefined wake-up command for a listening device. The wake-up command is a specific word or phrase that activates or triggers a response from the listening device. The system may also determine keywords within the digital content items, which may include the wake-up command or other relevant terms. This functionality enhances the system's ability to filter or prioritize content based on the presence of wake-up commands, improving the responsiveness and accuracy of voice-activated interactions. The system may be part of a larger digital assistant or content processing platform, where the detection of wake-up commands ensures seamless integration with voice-controlled devices. The invention aims to streamline the identification of actionable commands within digital content, reducing latency and improving user experience in voice-interactive systems.
Unknown
October 20, 2020
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